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利用 Python 进行数据分析:原书第 3 版
book

利用 Python 进行数据分析:原书第 3 版

by Wes McKinney
November 2023
Intermediate to advanced
512 pages
11h 53m
Chinese
China Machine Press
Content preview from 利用 Python 进行数据分析:原书第 3 版
pandas
入门
|
153
另一个常见的操作是将函数应用到由各列或各行所形成的一维数组上。
DataFrame
apply 方法可以实现此功能:
这里的函数 f 计算了
Series
最大值和最小值的差,在 frame 的每列都执行了一次。结果
是一个
Series
,使用 frame 的列作为索引。
如果传递 axis="columns" apply 函数,这个函数会在每行执行一次,可以将其当作
“跨列处理”:
许多最为常见的数组统计功能(如 sum mean)都是
DataFrame
的方法,因此无须使用
apply 方法。
传递到 apply 的函数不一定返回单个标量值,还可以返回由多个值组成的
Series
154
|
5
还可以使用元素级的
Python
函数。假如你想得到 frame 中各个浮点值的格式化字符串,
使用 applymap 即可:
之所以叫作 applymap,是因为
Series
有一个用于元素级函数的 map 方法:
5.2.6
排序和排名
根据特定条件对数据集排序也是一种重要的内置运算。要对行或列标签按字典顺序排
序,可使用 sort_index 方法,它将返回一个排好序的新对象:
pandas
入门
|
155
对于
DataFrame
,可以根据任意一个轴上的索引进行排序:
数据默认是按升序排序的,但也可以降序排序: ...
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Publisher Resources

ISBN: 9787111726722